article thumbnail

How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform

AWS Machine Learning

However, as a new product in a new space for Amazon, Amp needed more relevant data to inform their decision-making process. Part 1 shows how data was collected and processed using the data and analytics platform, and Part 2 shows how the data was used to create show recommendations using Amazon SageMaker , a fully managed ML service.

article thumbnail

Gone Virtual: Recap of the CETX Conference

Callminer

While it may not have been our typical, in-person experience filled with cocktail hours and outdoor activities, there was no shortage of entertainment and powerful and engaging insight from the customer experience (CX) and contact center industry’s most influential leaders, and hands-on practitioners. The great online kick-off.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Why Technology Won’t Help You Understand Your Customers

C3Centricity

A 2015 Capgemini and EMC study called “Big & Fast Data: The rise of Insight-Driven Business” showed that: 56% of the 1,000 senior decision makers surveyed claim that their investment in big data over the next three years will exceed past investment in information management.

article thumbnail

You’ve Got Data? Well Don’t Start There!

C3Centricity

A 2015 Capgemini and EMC study called “Big & Fast Data: The rise of Insight-Driven Business” showed that: 56% of the 1,000 senior decision makers surveyed claim that their investment in big data over the next three years will exceed past investment in information management.

article thumbnail

How Amp on Amazon used data to increase customer engagement, Part 2: Building a personalized show recommendation platform using Amazon SageMaker

AWS Machine Learning

Affinities are computed either implicitly from the user’s behavioral data or explicitly from topics of interest (such as pop music, baseball, or politics) as provided in their user profiles. This is Part 2 of a series on using data analytics and ML for Amp and creating a personalized show recommendation list platform.

article thumbnail

­­Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

AWS Machine Learning

Customers can also access offline store data using a Spark runtime and perform big data processing for ML feature analysis and feature engineering use cases. Table formats provide a way to abstract data files as a table. Apache Iceberg is an open table format for very large analytic datasets.

Scripts 80
article thumbnail

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

This data is information rich but can be vastly heterogenous. Proper handling of specialized terminology and concepts in different formats is essential to detect insights and ensure analytical integrity. With Knowledge Bases for Amazon Bedrock, you can access detailed information through simple, natural queries.

APIs 120